Microbial Electrosynthesis for Producing Medium Chain Fatty Acids

Chu, Na; Wen, Hao; Wu, Qinglian; Liang, Qinjun; Jiang, Yong; Liang, Peng; Ren, Zhiyong Jason; Zeng, Raymond J.

doi:10.1016/j.eng.2021.03.025

Cited by 42 publications

(25 citation statements)

References 168 publications

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“…Accordingly, there has been increased interest in recovering acetic acid from renewable sources (i.e., organic waste streams) to reduce the economic and environmental costs associated with acetic acid production . Many organic waste streams contain acetic acid, including acetylation industrial effluents (74–80% w/w), cellulose acetate production wastewater (35% w/w), terephthalic acid process wastewater (65% w/w), wood distillation effluents (1–8% w/w), and microbial fermentation process effluents (less than 10% w/w). ,,− In addition, acetic acid has been a major targeted product from organic waste and CO 2 valorization using emerging technologies such as arrested methanogenesis, microbial electrosynthesis, and electro-fermentation. − Although acetic acid and water mixtures do not form azeotropes, the relatively low volatility of acetic acid and their similar boiling points make their separation difficult. Traditional separation processes such as distillation and solvent extraction are energy- and cost-intensive, so new separation processes are needed, especially for selective acetic acid extraction from mixed products …”

Section: Introductionmentioning

confidence: 99%

Predicting Extraction Selectivity of Acetic Acid in Pervaporation by Machine Learning Models with Data Leakage Management

Yang

Zhu

McGaughey

et al. 2023

Environ. Sci. Technol.

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The extraction of acetic acid and other carboxylic acids from water is an emerging separation need as they are increasingly produced from waste organics and CO 2 during carbon valorization. However, the traditional experimental approach can be slow and expensive, and machine learning (ML) may provide new insights and guidance in membrane development for organic acid extraction. In this study, we collected extensive literature data and developed the first ML models for predicting separation factors between acetic acid and water in pervaporation with polymers' properties, membrane morphology, fabrication parameters, and operating conditions. Importantly, we assessed seed randomness and data leakage problems during model development, which have been overlooked in ML studies but will result in over-optimistic results and misinterpreted variable importance. With proper data leakage management, we established a robust model and achieved a root-mean-square error of 0.515 using the CatBoost regression model. In addition, the prediction model was interpreted to elucidate the variables' importance, where the mass ratio was the topmost significant variable in predicting separation factors. In addition, polymers' concentration and membranes' effective area contributed to information leakage. These results demonstrate ML models' advances in membrane design and fabrication and the importance of vigorous model validation.

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Section: Introductionmentioning

confidence: 99%

Predicting Extraction Selectivity of Acetic Acid in Pervaporation by Machine Learning Models with Data Leakage Management

Yang

Zhu

McGaughey

et al. 2023

Environ. Sci. Technol.

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“…However, MCFA production from CO 2 powered solely by the cathode is generally characterized by a low C6 specificity and a long lag phase. 85 To increase the overall performance, various strategies can be adopted, including constructing two-step systems (Figure 4a), 86 fabricating two-cathode reactors, 87 feeding SCFAs as an alternative to CO 2 , 88 and using organic waste as additional electron donors. 89 Despite the fact that ethanolguided MCFA-forming Clostridium kluyveri is not electroactive even in the presence of exogenous mediators, 90 results of enhanced MCFA production, with or without inserted electrodes, suggest that alternative routes and the associated mechanisms (e.g., redox or stress sensing) need to be clarified.…”

Section: T H Imentioning

confidence: 99%

“…With inserted electrodes, multiple stages (acidogenesis, solventogenesis, and chain elongation) involved in MCFA production can be integrated in a cathode chamber. However, MCFA production from CO 2 powered solely by the cathode is generally characterized by a low C6 specificity and a long lag phase . To increase the overall performance, various strategies can be adopted, including constructing two-step systems (Figure a), fabricating two-cathode reactors, feeding SCFAs as an alternative to CO 2 , and using organic waste as additional electron donors .…”

Section: Electricity-driven Metabolism Of Carbonmentioning

confidence: 99%

Electricity-Driven Microbial Metabolism of Carbon and Nitrogen: A Waste-to-Resource Solution

Chu

Jiang

Liang

et al. 2023

Environ. Sci. Technol.

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Electricity-driven microbial metabolism relies on the extracellular electron transfer (EET) process between microbes and electrodes and provides promise for resource recovery from wastewater and industrial discharges. Over the past decades, tremendous efforts have been dedicated to designing electrocatalysts and microbes, as well as hybrid systems to push this approach toward industrial adoption. This paper summarizes these advances in order to facilitate a better understanding of electricity-driven microbial metabolism as a sustainable waste-to-resource solution. Quantitative comparisons of microbial electrosynthesis and abiotic electrosynthesis are made, and the strategy of electrocatalyst-assisted microbial electrosynthesis is critically discussed. Nitrogen recovery processes including microbial electrochemical N 2 fixation, electrocatalytic N 2 reduction, dissimilatory nitrate reduction to ammonium (DNRA), and abiotic electrochemical nitrate reduction to ammonia (Abio-NRA) are systematically reviewed. Furthermore, the synchronous metabolism of carbon and nitrogen using hybrid inorganic-biological systems is discussed, including advanced physicochemical, microbial, and electrochemical characterizations involved in this field. Finally, perspectives for future trends are presented. The paper provides valuable insights on the potential contribution of electricity-driven microbial valorization of waste carbon and nitrogen toward a green and sustainable society.

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“…Recently, the use of mixed cultures has attracted the attention of researchers because it allows to obtain chemicals with higher economic value than acetate, like middlechain fatty acids (Tahir et al, 2021). However, there is no consensus in the scientific community about which strategy, whether mixed or pure culture, has more scalability opportunities since both have their pros and cons (Chu et al, 2021). Other products obtained by MES are biodegradable bioplastics, like polyhydroxyalkanoate (PHA) and poly (3-hydroxybutyrate) (PHB) (Dietrich et al, 2017).…”

Section: Waste To Chemicals With a Bioelectrosynthesis Cell (Besc)mentioning

confidence: 99%

Industrial bioelectrochemistry for waste valorization: State of the art and challenges

Maureira

Romero

Illanes

et al. 2023

Biotechnology Advances

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Microbial Electrosynthesis for Producing Medium Chain Fatty Acids

Cited by 42 publications

References 168 publications

Predicting Extraction Selectivity of Acetic Acid in Pervaporation by Machine Learning Models with Data Leakage Management

Predicting Extraction Selectivity of Acetic Acid in Pervaporation by Machine Learning Models with Data Leakage Management

Electricity-Driven Microbial Metabolism of Carbon and Nitrogen: A Waste-to-Resource Solution

Industrial bioelectrochemistry for waste valorization: State of the art and challenges

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